Table 7 shows the results of Jorgenson and Stiroh’s  growth accounting. In the 1979-85 period computers and peripherals contribute to output growth by 0.52% per year. In the 1985-92 period, the contribution is 0.38% per year. (The contribution dropped because the growth rate of real computer capital is lower for the 1979-1985 period than for the 1985-1992 period; nominal investment of computers did not increase much during the 1985-1992 period)
Information Technology and Productivity
Information Technology and Productivity:A Review of the Literature<br />By: Erik Brynjolfsson<br />ShinkyuYang<br />Presented by Chindavanh VILIVONG. School of Business, MIS, HanyangUniv<br />
Sub Content<br />I. The “Productivity Paradox”<br />A Clash of Expectations and Statistics<br />II. Research on the Productivity Effects of Information Technology<br />Economy-wide Productivity and Information Worker Productivity<br />Industry-Level Studies of Information Technology Productivity<br />Firm-Level Studies of Information Technology Productivity<br />Contribution to Consumer Surplus and Economic Growth<br />III. Remaining Paradox and Leading Explanations .<br /> Measurement Errors<br />Lags<br />Redistribution<br />Mismanagement<br />V. Conclusion<br />Summary<br />Where Do We Go From Here?<br />
I. The “Productivity Paradox” A Clash of Expectations and Statistics<br />
I. The “Productivity Paradox” A Clash of Expectations and Statistics<br />“No, computer do not boost productivity, at least not most of the time” [Economist, 1990].<br />“Computer Data Overload Limits Productivity Gains” [Zachary,1991].<br />“You can see the computer age everywhere but in the productivity statistics” [Robert Solow,1987].<br />“These studies have fueled a controversial debate, primarily because they have failed to document substantial productivity improvements attributable to information technology investments.” [Bakos and Kemerer, 1992]<br />
What is Productivity Paradox?<br />- “Solow computer paradox “<br /> - Discrepancy between measures of investment in information technology and measures of output at the national level<br />
Definitions:<br />Information technology: Office, Computing and Accounting Machinery (OCAM) which consists primarily of computers. <br />Information Processing Equipment (IPE): communications equipment, scientific and engineering instruments, photocopiers and related equipment. <br />Labor productivity is calculated as the level of output divided by a given level of labor input. <br />Multifactor productivity is calculated as the level of output for a given level of several inputs, typically labor, capital and materials. <br /> Productivity calculations, “output” is defined as the number of units produced times their unit value.<br />
Trends:<br />The price of computing has dropped by half every 2-3 years.<br />There have been increasing levels of business investment in information technology equipment. <br />Information processing continues to be the principal task undertaken by America’s work force. <br />Overall productivity has slowed significantly since the early 1970s and measured productivity growth has fallen.<br />White collar productivity statistics have been essentially stagnant for 20 years.<br />
Two central questions<br />1. Why would companies invest so heavily in information technology if it didn’t add to productivity? <br />2. If information technology is contributing to productivity, why is it so difficult to measure it?<br />
II. Research on the Productivity Effects of Information Technology<br />
A. Economy-wide Productivity and Information Worker Productivity<br /> Issue:<br />The productivity slowdown began in the early1970s. <br /> Labor productivity growth dropped from about 2.5% per year for 1953-1968 to about 0.7% per year for 1973-1979.<br /> Multi-factor productivity growth declined from 1.75% a year to 0.32%.<br />The sharp drop in productivity roughly coincided with the rapid increase in the use of information technology. <br />Past: Office work was not very capital intensive.<br />Recently: white collar (information worker) has begun approaching of production capital per (“blue collar”) production worker. <br />Concurrently, the ranks of information workers have ballooned and the ranks of production workers have shrunk<br />
A. Economy-wide Productivity and Information Worker Productivity (Cont.)<br />2. Size of Puzzle<br /><ul><li>In 1992, IT capital stock (OCAM) was equal to about 10% of GNP, when the base year is 1987.
It takes over 30 years. So it’s difficult to isolate because other factors affected (turbulent in 1970s and early 1980s).
A slightly higher contribution for 1979-1992 period are 0.38% - 0.52% per year. [Jorgenson and Stiroh, 1995]
Productivity improvement may be involved in the recent “jobless recovery” of the US economy.</li></li></ul><li>A. Economy-wide Productivity and Information Worker Productivity (Cont.)<br />3. Information Workers with Computers.<br /><ul><li>Relative productivity cannot be directly assumed from the number of information workers per unit output.
Economic growth may slow down because of intrinsically slow technical progress in the white collar sector, since it is less subject to automation.</li></li></ul><li>A. Economy-wide Productivity and Information Worker Productivity (Cont.)<br /><ul><li>Why white collar sector’s share in economy growing?
Why are companies investing so heavily in IT if it doesn’t add productivity?</li></ul> - They are forced to, at least in developed countries.<br /> In short, IT may not be a source of the productivity slowdown, but simply a response to the overall transformation of the economy. <br />
A. Economy-wide Productivity and Information Worker Productivity (Cont.)<br />Contrasting the economy-wide productivity slowdown with increasing IT investment is an obtuse approach, because so many other factors may intervene periods. <br />The firm-level helps to control many problems from aggregation, but it is often difficult to find data representative for the whole economy<br />
B. Industry-Level Studies of Information Technology Productivity<br />
B. Industry-Level Studies of Information Technology Productivity (Cont.)<br />Two possible sources of measurement error.<br />The first kind of error occurs when computer price and quantity are measured with error.<br />The second source of error is more delicate. Observes that computers may exacerbate errors in the measurement of productivity: firms invest in computers not only for cost reduction but also for quality improvement. <br />
C. Firm-Level Studies of Information Technology Productivity<br />
C. Firm-Level Studies of Information Technology Productivity (Cont.)<br />
D. Contribution to Consumer Surplus and Economic Growth<br />
D. Contribution to Consumer Surplus and Economic Growth (Cont.)<br />
III. Remaining Paradox and Leading Explanations<br />IT’s contribution to output and productivity is documented in several important studies, but whether or not this output growth is beneficial to profits and market value is not yet clear.<br /> Some practitioners and researchers still believe that “the full power of the computer in increasing national productivity has not yet unfolded.” In this sense, the productivity paradox still awaits explanation<br />1) Mismeasurementof outputs and inputs,<br />2) Lags due to learning and adjustment,<br />3) Redistribution and dissipation of profits,<br />4) Mismanagement of information and technology.<br />
A. Measurement Errors<br />The easiest explanation for the confusion about the productivity of information technology is imply that we are not properly measuring output.<br />Measurement errors need not necessarily bias IT productivity if they exist in comparable magnitudes both before and after IT investments. <br />
B. Lags<br />the benefits from information technology can take several years to appear on the bottom line.<br />
C. Redistribution<br />Information technology may be beneficial to individual firms, but unproductive from the standpoint of the industry or the economy as a whole.<br />
D. Mismanagement<br />The decision-makers aren’t acting in the interests of the firm. Instead, they are<br />a) increasing their slack, <br />b) signaling their prowess or <br />c) simply using outdated criteria for decision-making.<br />
V. Conclusion<br />A. Summary<br />Relationship between the productivity slowdown of the whole US economy and the rapid growth of computer capital<br />Poor data quality for IT outputs and inputs has exacerbated this problem<br />
Remaining paradox<br />1. Measurement Error: Outputs (and inputs) of information-using industries are not being properly measured by conventional approaches.<br />2. Lags: Time lags in the pay-offs of information technology make analysis of current costs versus current benefits misleading.<br />3. Redistribution: Information technology is especially likely to be used in redistributive activities among firms, making it privately beneficial without adding to total output.<br />4. Mismanagement: The lack of explicit measures of the value of information make it particularly vulnerable to misapplication and overconsumption by managers.<br />
Where Do We Go From Here?<br />1. Must be improving the data and measurement techniques.<br />Correcting for the potential lags in the impact of IT is conceptually easier.<br />The redistribution hypothesis can be examined in two ways.<br />2. To compare various measures of a firm’s performance with its competitors’ IT spending<br />